diff --git a/INFO_DP.bib b/INFO_DP.bib
index 899048f..7d56ec9 100644
--- a/INFO_DP.bib
+++ b/INFO_DP.bib
@@ -2,13 +2,27 @@
 %% http://bibdesk.sourceforge.net/
 
 
-%% Created for Nigel Stanger at 2011-05-06 11:22:11 +1200 
+%% Created for Nigel Stanger at 2011-07-25 16:59:08 +1200 
 
 
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+@techreport{dp2011-05,
+	Abstract = {In Normative Multi-Agent Systems (NorMAS), researchers have investigated several mechanisms for agents to learn norms. In the context of agents learning norms, the objectives of the paper are three-fold. First, this paper aims at providing an overview of different mechanisms employed by researchers for norm learning. Second, it discusses the contributions of different mechanisms to the three aspects of active learning namely learning by doing, observing and com- municating. Third, it compares two normative architectures which have an emphasis on the learning of norms. It also discusses the features that should be considered in future norm learning architectures.},
+	Address = {Dunedin, New Zealand},
+	Author = {Bastin Tony Roy Savarimuthu},
+	Date-Added = {2011-07-25 16:39:52 +1200},
+	Date-Modified = {2011-07-25 16:39:52 +1200},
+	Institution = {Department of Information Science, University of Otago},
+	Keywords = {norms, learning, agents, mechanisms},
+	Month = may,
+	Number = {2011/05},
+	Title = {Norm learning in multi-agent societies},
+	Type = {Discussion paper},
+	Year = {2011}}
+
 @techreport{dp2011-04,
 	Abstract = {Previous research on modelling and monitoring norms, contracts and commitments has studied the semantics of concepts such as obligation, permission, prohibition and commitment; languages for expressing behavioural constraints (such as norms or contracts) to be followed by agents in specific contexts; and mechanisms for run-time monitoring of fulfilment and violation of these constraints. However, there has been little work that provided all of these features while also allowing the current expectations of agents, and the fulfilment and violation of these expectations to be expressed as first-class constructs in the language. This paper demonstrates the benefits of providing this capability by considering a variety of use cases and demonstrating how these can be addressed as applications of a previously defined temporal logic of expectations and an associated monitoring technique.},
 	Address = {Dunedin, New Zealand},
@@ -76,17 +90,17 @@
 	Type = {Discussion paper},
 	Year = {2010}}
 
-@techreport{dp2011-05,
-	Abstract = {In Normative Multi-Agent Systems (NorMAS), researchers have investigated several mechanisms for agents to learn norms. In the context of agents learning norms, the objectives of the paper are three-fold. First, this paper aims at providing an overview of different mechanisms employed by researchers for norm learning. Second, it discusses the contributions of different mechanisms to the three aspects of active learning namely learning by doing, observing and com- municating. Third, it compares two normative architectures which have an emphasis on the learning of norms. It also discusses the features that should be considered in future norm learning architectures.},
+@techreport{dp2011-06,
+	Abstract = {Over the last few years, the voluminous increase in the academic research publications has gained significant research attention. Research has been carried out exploring novel ways of providing information services using the research content. However, the task of extracting meaningful information from research documents remains a challenge. This paper presents our research work carried out for developing intelligent information systems, exploiting the research content. We present in this paper, a linked data application which uses a new semantic publishing model for providing value added information services for the research community. The paper presents a conceptual framework for modelling contexts associated with sentences in research articles and discusses the Sentence Context Ontology, which is used to convert the information extracted from research documents into machine-understandable data. The paper also reports on supervised learning experiments carried out using conditional probabilistic models for achieving automatic context identification.},
 	Address = {Dunedin, New Zealand},
-	Author = {Bastin Tony Roy Savarimuthu},
+	Author = {M.A. Angrosh and Stephen Cranefield and Nigel Stanger},
 	Date-Added = {2010-11-17 14:50:10 +1300},
-	Date-Modified = {2011-05-06 10:38:53 +1200},
+	Date-Modified = {2011-07-25 16:47:40 +1200},
 	Institution = {Department of Information Science, University of Otago},
-	Keywords = {norms, learning, agents, mechanisms},
-	Month = may,
-	Number = {2011/05},
-	Title = {Norm learning in multi-agent societies},
+	Keywords = {semantic publishing models, sentence context ontology, linked data application, conditional random fields, maximum entropy markov models, citation classification, sentence context identification},
+	Month = jul,
+	Number = {2011/06},
+	Title = {Contextual information retrieval in research articles: Semantic publishing tools for the research community},
 	Type = {Discussion paper},
 	Year = {2011}}